Multi-Area Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network Shmuel Oren University of California , Berkeley Joint work with Anthony Papavasiliou Presented at DIMACS Workshop on Energy Infrastructure DIMACS Center, Rutgers University February 20-22, 2013 Uncertainty Negative Correlation with Load 8000 250 7000 load 6000 150 5000 100 4000 50 0 load (MW) wind power output (MW) 200 wind power 24 48 72 96 hour 120 144 168 3000 3 All Rights Reserved to Shmuel Oren Conventional Solution Source: CAISO The DR Alternative to Expanding Flexible Thermal Generation Alternative DR Paradigms Alternative Approaches to DR Mobilization Evaluation Methodology • Comparison requires explicit accounting for uncertainty for consistent determination of locational reserves. • Stochastic unit commitment optimization accounts for uncertainty by considering a limited number of probabilistic wind and contingency scenarios, committing slow reserves early with fast reserves and demand response adjusted after uncertainties are revealed. • Economic and reliability outcomes are calculated using Monte Carlo simulation with large number of probabilistic scenarios and contingencies 9 Model Structure 10 Unit Commitment The Real Thing Two Stage Stochastic Unit Commitment Scenario Selection Decomposition Parallelization Scenario Selection Wind Modeling and Data Sources Model Calibration Data Fit WECC Case Study Case Study Summary Day Types Competing Reserve Rules Reserve Policy Comparison Deep Integration, No Transmission, No Contingencies Reserve Policy Comparison No Wind Reserve Policy Comparison Moderate Integration Reserve Policy Comparison Deep Integration Summary Demand Response Study Centralized Load Dispatch Firm Demand Uncertainty Market Based: Demand Side Bidding Implementation of Coupling Price and Wind Data For Coupling Model Coupling Model (Smart Charging) Dynamic Programming With Recombinant Lattices Demand Response Results Conclusions References • • • • • • • • • Papavasiliou Anthony, Shmuel Oren and Richard O’Neill, “Reserve Requirements for Wind Power Integration: A Scenario-Based Stochastic Programming Framework”, IEEE Transactions on Power System, Vol 26, No4 (2011), pp. 2197-2206 Papavasiliou A. and S. S. Oren, ”Integrating Renewable Energy Contracts and Wholesale Dynamic Pricing to Serve Aggregate Flexible Loads” Invited Panel Paper, Proceeding of the IEEE PES GM, Detroit, Michigan, July 24-28, 2011. Papavasiliou A. and S. S. Oren “Integration of Contracted Renewable Energy and Spot Market Supply to Serve Flexible Loads”, Proceedings of the 18th World Congress of the International Federation of Automatic Control, August 28 – September 2, 2011, Milano, Italy. Papavasiliou A.and S. S. Oren, “Stochastic Modeling of Multi-area Wind Power Production “, Proceedings of PMAPS 2012, Istanbul Turkey, June 10-14, 2012. Oren S. S., Invited Panel Paper ” Renewable Energy Integration and the Impact of Carbon Regulation on the Electric Grid “, Proceeding of the IEEE PES GM, San Diego CA, July 22-26, 2012. Papavasiliou A., S. S. Oren, ” A Stochastic Unit Commitment Model for Integrating Renewable Supply and Demand Response” Invited Panel Paper, Proceeding of the IEEE PES GM, San Diego, CA, July 24-28, 2012. Papavasiliou A., S. S. Oren, “Large-Scale Integration of Deferrable Demand and Renewable Energy Sources in Power Systems”, Accepted for publication in a special issue of the IEEE PES Transaction. Papavasiliou A., S. S. Oren, “Multi-Area Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network”, Accepted for publication in Journal of Operations Research. Papavasiliou Anthony, Shmuel Oren, Barry Rountree “Applying High Performance Computing to Multi-Area Stochastic Unit Commitment for Renewable Energy Integration”, Submitted to Mathematical Programming (February 2013) 40 Questions?